NuWave blends cutting-edge technology with investment theory predicated on the behavioral tendencies of market participants.

Long a pioneer in the application of artificial intelligence and machine learning to financial modeling, NuWave develops models which identify the dominant directional price opportunity for a given market or security. The majority of our strategies pursue both long and short opportunities equally, and all NuWave portfolios are actively managed. In the last decade, significant advances in computing power and the development of increasingly sophisticated AI modeling concepts have continued to shape NuWave’s systematic approach to trading.

By way of analogy, consider the incredible advances made in terms of machine-based speech recognition. Ten years ago, machines were capable of only a rudimentary understanding of speech – the only acceptable responses being “Yes”, “No” or “Representative” . . . five years ago, the range of responses was somewhat broader, consisting of certain phrases or specific sentences . . .

Today, the machine is capable of “understanding” virtually any response. Similarly, personal assistants, such as Siri and Google, understand queries, perform tasks, follow instructions – all from conversational speech.

Building on the example of speech recognition, NuWave applies machine learning and AI to better understand the language of financial and commodity markets. It is undeniable that the markets speak a distinct language . . . a language that we – along with many others – are trying to decipher.

Different asset managers may utilize different methods of analysis or focus on different data, but we all share the same goal – to better understand what the markets are saying and, in doing so, to identify potential trading opportunities.

Each piece of data, whether technical or fundamental, is analogous to an individual syllable . . . and multiple data points, like multiple syllables, form words and sentences which, in turn, form paragraphs – all of which help to describe, and ultimately forecast, directional price behaviors.

There are infinite ways to parse and aggregate feature-rich information. Consider technical features such as volatility, seasonality, sequential patterns and directionality, or possibly fundamental data relating to the economy or a corporate balance sheet – there are countless ways to define or categorize such data sets and determine which combinations of relevant data sets are meaningful.

Essentially, advanced machine learning and AI concepts can compare and interpret combinations of data throughout history to determine which combinations are likely to yield high probability directional price outcomes. Simply put, machine learning and AI help us better understand what the market is telling us.